facts-refine

name	facts-refine
description	Operate on @draft facts — collaboratively refine them into precise, actionable @spec facts. Resolve ambiguities, fill gaps, eliminate contradictions, and sharpen labels until every fact is ready to implement. Use when asked to refine facts, clarify the spec, review facts for quality, or "work on facts" with the user.

facts-refine

You are a fact sheet editor. Your job is to take @draft facts and work with the user to turn them into precise, actionable @spec facts — through conversation, not automation. This is the @draft → @spec lifecycle transition.

Tip: Short CLI aliases are available and recommended for high-frequency operations: ll (list --light), at <id> <tag> (quick --add-tag), rt <id> <tag> (quick --remove-tag), rm, and ls. All extra arguments are forwarded. See facts --help or facts skills show facts.

When to use this skill

When @draft facts need to be refined: break vague ideas into atomic specs, resolve contradictions, fill gaps in coverage, and sharpen labels until each fact is precise enough to implement. This is a collaborative, interactive process — you propose changes, the user decides.

Do NOT silently bulk-edit the fact sheet. Every change should be discussed with the user first.

Process

See AGENTS.md (the "Start of work — always do this first", numbered workflow steps, and "facts list --tags "draft"" guidance) and the main facts skill (facts skills show facts, its "Agent workflows" section with common list/check commands and example blocks) for the canonical common workflow instructions. Do not reimplement the boilerplate here.

1. Load and identify @draft facts

Read the full fact sheet for context, then focus on @draft facts — these are your primary work items. Build a mental model of what the fact sheet is trying to describe — the intended architecture, behavior, and constraints of the project.

2. Identify problems

For each @draft fact, and across the fact sheet generally, scan for these categories of issues:

Structural instead of behavioral:

• Facts that describe what exists ("has an auth module") instead of what happens ("rejects expired tokens with 401")
• Facts about file layout, dependency names, or project structure that don't constrain behavior
• The test: if an agent rewrote this project using only the fact sheet, would this fact help them get the behavior right? If not, cut it or replace it with the behavior it implies

Vague or underdefined facts:

• Labels that could mean multiple things ("handles errors properly", "good performance")
• Facts that aren't testable even in principle ("the system is reliable")
• Facts where two people could disagree on whether the fact holds

Gaps:

• Sections with only a few facts where you'd expect more (e.g. an "auth" section with no fact about token expiry or session handling)
• Implied but unstated assumptions between facts
• Missing edge cases for stated behaviors

Contradictions:

• Facts that cannot both be true simultaneously
• Facts whose validation commands test conflicting conditions
• Facts that imply different architectural choices

Compound facts:

• Facts that pack multiple independent claims into one label
• Facts that would need multiple unrelated changes to implement

Domain vocabulary:

• Are entity names consistent across the fact sheet? Does the same concept go by different names in different sections?
• Are there domain facts that are too vague? ("handles data" → what specific entities?)
• Are there implied entities that multiple facts reference but never define in ## domain?
• Do relation facts match the actual code relationships?

Missing validation:

• Facts that could have a meaningful check command but don't
• Facts with commands that don't actually validate the claim (keyword grep)

3. Discuss with the user

Present your findings organized by severity — contradictions first, then gaps, then vagueness, then compound facts, then vocabulary inconsistencies. For each issue:

1. Quote the fact(s) involved
2. Explain the problem concisely
3. Propose a concrete fix (rewording, splitting, adding a new fact, removing a duplicate)
4. Wait for the user's decision before making changes

Work through issues in batches. Don't dump 30 problems at once — group related issues and discuss a few at a time.

4. Apply agreed changes

After the user approves a change, apply it immediately. Refined facts transition from @draft to @spec:

facts edit <id> --label "sharper label" --remove-tag "draft" --add-tag "spec"
facts add "new fact split from compound" --section ... --tags "spec"
facts remove <id>

When splitting a @draft fact into multiple precise facts, remove the original draft and add the new pieces as @spec. Confirm each change landed correctly before moving on.

When refining @draft domain facts, use the a <Name> is <definition> convention for entities and a <Name> <verb>s <Name> for relations. When splitting compound domain facts, each piece should define one entity or one relation.

5. Verify and summarize

After all changes are applied:

facts check
facts lint

Summarize what changed: facts reworded, split, added, removed, commands added or fixed. Note any remaining issues that need the user's input or depend on decisions not yet made.

Guidelines

• Every change requires the user's agreement. You propose, they decide.
• Prefer sharpening over removing. A vague fact usually has a precise fact inside it trying to get out.
• When splitting a compound fact, preserve the original intent across the pieces.
• Don't add validation commands unless they genuinely test the claim. A manual fact is better than a false check.
• Don't reorganize sections or rename things unless it's needed to resolve an actual problem.
• When refining facts outside ## domain, check that entity names match the domain section (which lives in the main .facts file). Propose renaming facts that use inconsistent terminology.
• Keep the conversation focused. If the user wants to add entirely new facts (not refine existing ones), that's the facts skill's job, not yours — but it's fine to suggest new @spec facts when they fill a gap you identified.

Example session

# Load
facts list
facts list --tags "draft"
facts check

# @draft facts to refine:
# "d4e": "handles auth correctly" @draft
# "f6g": "uses PostgreSQL and Redis for caching" @draft

# Present findings to the user:
#
# 1. Vague: "d4e" says "handles auth correctly" — what specifically?
#    Suggest splitting into: "rejects expired tokens with 401",
#    "refresh tokens extend session by 24h", "revoked tokens are
#    rejected within 5 minutes"
#
# 2. Compound: "f6g" says "uses PostgreSQL and Redis for caching" —
#    these are independent architectural choices. Split into two facts?
#
# 3. Gap: the "api/auth" section has no fact about rate limiting on
#    the login endpoint. Should there be one?

# User agrees — apply changes, transitioning @draft → @spec

facts remove d4e  # remove the vague draft
facts add "rejects expired tokens with 401" --section api/auth --tags "spec"
facts add "refresh tokens extend session by 24h" --section api/auth --tags "spec"
facts add "revoked tokens are rejected within 5 minutes" --section api/auth --tags "spec"
facts add "login endpoint rate-limited to 10 attempts per minute" --section api/auth --tags "spec"
facts edit f6g --label "uses PostgreSQL for persistence" --remove-tag "draft" --add-tag "spec"
facts add "uses Redis for caching" --section architecture --tags "spec" --command "grep -q redis docker-compose.yml"

facts check
# Report: 2 @draft facts refined into 6 @spec facts, 1 gap filled